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Semantic Annotation of Mobility Data using Social Media

Authors:

Wang-Chien Lee,

Zhuojie HuangAuthors Info & Claims

WWW '15: Proceedings of the 24th International Conference on World Wide Web

Pages 1253 - 1263

https://doi.org/10.1145/2736277.2741675

Published: 18 May 2015 Publication History

Abstract

Recent developments in sensors, GPS and smart phones have provided us with a large amount of mobility data. At the same time, large-scale crowd-generated social media data, such as geo-tagged tweets, provide rich semantic information about locations and events. Combining the mobility data and surrounding social media data enables us to semantically understand why a person travels to a location at a particular time (e.g., attending a local event or visiting a point of interest). Previous research on mobility data mining has been mainly focused on mining patterns using only the mobility data. In this paper, we study the problem of using social media to annotate mobility data. As social media data is often noisy, the key research problem lies in using the right model to retrieve only the relevant words with respect to a mobility record. We propose frequency-based method, Gaussian mixture model, and kernel density estimation (KDE) to tackle this problem. We show that KDE is the most suitable model as it captures the locality of word distribution very well. We test our proposal using the real dataset collected from Twitter and demonstrate the effectiveness of our techniques via both interesting case studies and a comprehensive evaluation.

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Cited By

Zou XYan YHao XHu YWen HLiu EZhang JLi YLi TZheng YLiang Y(2025)Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlookInformation Fusion10.1016/j.inffus.2024.102606113(102606)Online publication date: Jan-2025
https://doi.org/10.1016/j.inffus.2024.102606
Honzák KSchmidt SResch BRuthensteiner P(2024)Contextual Enrichment of Crowds from Mobile Phone Data through Multimodal Geo-Social Media AnalysisISPRS International Journal of Geo-Information10.3390/ijgi1310035013:10(350)Online publication date: 3-Oct-2024
https://doi.org/10.3390/ijgi13100350
Darányi ARuppert TAbonyi J(2024)Particle filtering supported probability density estimation of mobility patternsHeliyon10.1016/j.heliyon.2024.e29437(e29437)Online publication date: Apr-2024
https://doi.org/10.1016/j.heliyon.2024.e29437
Show More Cited By

Index Terms

Semantic Annotation of Mobility Data using Social Media
1. Applied computing
  1. Document management and text processing

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Published In

cover image ACM Other conferences

WWW '15: Proceedings of the 24th International Conference on World Wide Web

May 2015

1460 pages

ISBN:9781450334693

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Copyright © 2015 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 18 May 2015

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WWW '15

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WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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WWW '15 Paper Acceptance Rate 131 of 929 submissions, 14%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Zou XYan YHao XHu YWen HLiu EZhang JLi YLi TZheng YLiang Y(2025)Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlookInformation Fusion10.1016/j.inffus.2024.102606113(102606)Online publication date: Jan-2025
https://doi.org/10.1016/j.inffus.2024.102606
Honzák KSchmidt SResch BRuthensteiner P(2024)Contextual Enrichment of Crowds from Mobile Phone Data through Multimodal Geo-Social Media AnalysisISPRS International Journal of Geo-Information10.3390/ijgi1310035013:10(350)Online publication date: 3-Oct-2024
https://doi.org/10.3390/ijgi13100350
Darányi ARuppert TAbonyi J(2024)Particle filtering supported probability density estimation of mobility patternsHeliyon10.1016/j.heliyon.2024.e29437(e29437)Online publication date: Apr-2024
https://doi.org/10.1016/j.heliyon.2024.e29437
Pal AWang JWu YKant KLiu ZSato K(2023)Social Media Driven Big Data Analysis for Disaster Situation Awareness: A TutorialIEEE Transactions on Big Data10.1109/TBDATA.2022.31584319:1(1-21)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3158431
Liu YAo XDong LZhang CWang JHe Q(2023)Spatiotemporal Activity Modeling via Hierarchical Cross-Modal Embedding : Extended Abstract2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00334(3815-3816)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00334
Diaz JBravo-Marquez FPoblete B(2022)Language Modeling on Location-Based Social NetworksISPRS International Journal of Geo-Information10.3390/ijgi1102014711:2(147)Online publication date: 18-Feb-2022
https://doi.org/10.3390/ijgi11020147
Akavia ALeibovich MResheff YRon RShahar MVald M(2022)Privacy-Preserving Decision Trees Training and PredictionACM Transactions on Privacy and Security10.1145/351719725:3(1-30)Online publication date: 19-May-2022
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Iyer PMasoumzadeh A(2022)Learning Relationship-Based Access Control Policies from Black-Box SystemsACM Transactions on Privacy and Security10.1145/351712125:3(1-36)Online publication date: 19-May-2022
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Fischer AFuhry BKußmaul JJanneck JKerschbaum FBodden E(2022)Computation on Encrypted Data Using Dataflow AuthenticationACM Transactions on Privacy and Security10.1145/351300525:3(1-36)Online publication date: 19-May-2022
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Li HLu HJensen CTang BCheema M(2022)Spatial Data Quality in the Internet of Things: Management, Exploitation, and ProspectsACM Computing Surveys10.1145/349833855:3(1-41)Online publication date: 3-Feb-2022
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